快速傅里叶变换
不变(物理)
指数
计算复杂性理论
算法
计算机科学
傅里叶变换
图像(数学)
人工智能
计算机视觉
模式识别(心理学)
数学
数学分析
数学物理
语言学
哲学
作者
Ziliang Ping,Yongjing Jiang,Suhua Zhou,Yu Wu
摘要
Orthogonal multi-distorted invariant Complex Exponent Moments (CEMs) are proposed. A fast and accurate 2-D Fast Fourier Transform (FFT) algorithm is used to calculate CEMs. Theoretical analysis is presented to demonstrate the multi-distorted invariant property of CEMs. The proposed method is applied in the pattern recognition of human faces, English letters and Chinese characters. Experimental results show that CEMs have higher quality and lower computational complexity than RHFMs in image reconstruction and pattern recognition.
科研通智能强力驱动
Strongly Powered by AbleSci AI